Credit Card Fraud Detection Platforms: Optimizing Security Efficiency

Fraud is a pervasive issue in several sectors across the world. Be it healthcare, e-commerce, or finance. While technological advancements such as tokenization and multi-factor authentication have improved security, credit card fraud is a persistent challenge. A major contributor to this is the ever-evolving landscape of fraudulent activities.

Credit card fraud detection platforms help address this issue by combining various tools and technologies. Want to know more about how these platforms work? This blog post has it all. We cover the essentials of these platforms and detail the major drivers of the credit card fraud detection platform market. Let’s dive in!

What Are Credit Card Fraud Detection Platforms?

Credit card fraud detection platforms combine several processes, tools, and technologies. These platforms help prevent unauthorized purchases. They are useful in both physical and online environments. Credit card fraud detection platforms verify that the cardholder is indeed the one they claim to be. They also confirm the legitimacy of each transaction made. These platforms make use of several detection methods. They can range from basic authentication to advanced analytics enabled by solutions from the machine learning platforms market.

How Are Credit Card Numbers Accessed by Fraudsters?

Fraudsters may be able to access credit card numbers on illicit marketplaces. The numbers can sometimes be available for just a few dollars. There are several methods used by criminals to access credit card numbers. These include:

Theft: Here, physical stealing of the card takes place. Sometimes, they may be able to get access to cards through theft.

Skimming and Cloning: Skimming is used by fraudsters to capture the card details from their owner. This makes it possible for them to create unauthorized copies.

Account Takeover: Criminals may be able to get unauthorized access to the account that’s linked to the credit card. The situation here may get exacerbated if the linked account also functions as an e-wallet.

Phishing and Social Engineering: Scammers go with the exploitation of human psychology for getting sensitive information. They do so through SMS, deceptive emails, or fake online stores.

Infiltrating Legitimate Online Stores: Criminals use the online skimming method for the injection of malicious scripts into existing e-commerce websites. Sophisticated tools such as MageCart are often used for the same.

What Are Key Market Metrics?

At Polaris Market Research, we’ve done an in-depth assessment of the rapidly evolving credit card fraud detection platform market. Our analysis reveals that the market for these platforms is anticipated to account for a CAGR of 15.3% from 2025 to 2034.

The increased use of electronic payment systems has exposed financial systems to higher risks of fraud. This has created a need for platforms that can detect fraud. Additionally, the rapid expansion of e-commerce and the growing use of contactless payments are contributing to the credit card fraud detection platform market expansion.

How Are Credit Card Frauds Detected?

Card Security Features

A number of security features have been developed by credit card networks for the prevention of fraudulent purchases. Address verification service (AVS) is used for card networks for verifying the identity of the cardholder. AVS does this by cross-referencing the registered address with that of the bank records. 3DS is another widely used credit card feature. 3DS functions as a security layer where users need to enter a code to complete the transaction. CVV is a three-digit card code that confirms the possession of the card during purchase.

Risk Scoring

Risk scoring is a standard method for evaluating the risk of a transaction. The risk is assessed based on various factors. These include location, transaction amount, past behavior, and frequency. They allow businesses to make informed decisions about whether to allow a payment. Higher risk scores indicate an increased likelihood of fraud. By assessing risk scores, organizations can focus on specific accounts or transactions that require further investigation.

Digital Footprint Analysis

The confirmation of a user’s online identity is important to prevent fraudulent transactions. Importantly, this must be done without adding friction to the user transaction process. Digital footprint analysis acts as an invisible security layer. It collects additional information from single data points. Digital and social checks help examine if the contact information is the same as that of registered digital and social accounts. IP analysis checks for connections from suspicious proxies or virtual private networks. BIN lookup verifies whether the payment card type aligns with the expected patterns of usage. Device intelligence is used for analyzing data about the devices used for accessing the platform.

Network Analysis

Fraudsters often rely on collaboration and network formation for carrying out their activities. Machine learning techniques, such as graph analysis, can help in uncovering these networks. They do so through the analysis of relationships between entities and the identification of unusual clusters or connections.

How is AI impacting the Credit Card Fraud Detection Platform Market?

The AI in cybersecurity market is reshaping the market for credit card fraud detection. Behavioral analytics enabled by AI models creates individual spending profiles and reduces false positives by a significant amount. The ability of AI to process billions of transactions in seconds allows for the effective handling of the growing volume of digital payments. AI can recognize non-linear patterns that may get overlooked by traditional rule-based systems. Furthermore, AI enables instant risk scoring, making it possible for financial institutions to block transactions before they are carried out.

To Conclude

Credit card fraud occurs when someone gains unauthorized access to a card and uses it to make purchases. Credit card fraud detection platforms help address this challenge. Advancements in technology have made it possible for these platforms to detect fraud in real-time. In the coming years, we can expect to see increased investments and partnerships in the credit card fraud detection platform market for improved accuracy and scalability.